Steve blank moneyball and evidence-based entreprenuership Stanford University
The document discusses the Lean Startup methodology and the development of an Investment Readiness Level (IRL) framework analogous to NASA's Technology Readiness Level. It describes how the IRL evaluates a startup's progress based on data, moving from the initial hypothesis stage through validating the problem and solution fit, and product/market fit on both sides of the Business Model Canvas. The IRL is intended to quantify risk levels for startups based on evidence gathered through customer development and experimentation.
The document summarizes the journey of four engineers who went through Stanford's Lean LaunchPad class to develop an MVP for a startup idea. Over nine weeks, they tested several hypotheses through customer interviews but were unable to find product-market fit. Their final idea involved personalized recipe recommendations but they determined it was not a viable business due to high customer acquisition costs and an unproven revenue model. They learned important lessons about customer discovery, competition, and the importance of prioritizing revenue.
The document discusses lean innovation and continuous innovation. It argues that continuous disruption requires continuous innovation, and that continuous innovation requires new management tools like lean innovation management. Lean innovation aims to achieve 10x the number of initiatives in 1/5 the amount of time through techniques like the business model canvas, customer development, and agile engineering. It also discusses the need for ambidextrous organizations that can both execute current business models while pursuing breakthrough innovations. Examples are provided of how lean startup techniques have been applied in practice, including a case study of a Stanford student team that applied customer development to validate and pivot their business model based on customer interviews.
The document discusses evidence-based entrepreneurship and investment readiness levels (IRL). It presents the Lean Startup methodology, customer development, business model canvas, agile engineering and hypotheses testing as part of the evidence-based methodology. It discusses how IRL can assess project maturity similar to NASA's technology readiness levels (TRL) by focusing on data from experiments and customer interviews. Several examples are presented of teams applying this methodology in NSF programs to validate hypotheses, the business model and determine IRL.
Over the course of 9 weeks, the team went through multiple pivots to find product-market fit:
1. They started with facial recognition for smart door locks but learned their solution did not fully address parent concerns.
2. Their second pivot was to enterprise access control but customers said tailgating was a bigger problem.
3. Recognizing tailgating risks required surveillance, they pivoted again to surveillance software.
4. After failing to find problem-team fit, they did a complete restart and developed an AI assistant for streamlining similar work tasks. Customer feedback was positive and they identified a potential market of 500k ML professionals.
Becoming an Enterprise SaaS Company | DecisionDesk @ TechPintJohn Knific
DecisionDesk provides SaaS solutions for streamlining digital admissions processes for higher education institutions. After initial success with online portfolios, they pivoted to focus on larger deals, but struggled with a massive implementation that required rewriting their product. They learned that discovery is cheaper than late discovery, experience is better than being scrappy, and to focus on either SMB or enterprise markets, not both. They now have a process of specialized roles to properly execute large deals and target the right decision makers to avoid getting bogged down in price negotiations.
business model, business model canvas, mission model, mission model canvas, customer development, lean launchpad, lean startup, stanford, startup, steve blank, entrepreneurship, I-Corps, Stanford
Steve blank moneyball and evidence-based entreprenuership Stanford University
The document discusses the Lean Startup methodology and the development of an Investment Readiness Level (IRL) framework analogous to NASA's Technology Readiness Level. It describes how the IRL evaluates a startup's progress based on data, moving from the initial hypothesis stage through validating the problem and solution fit, and product/market fit on both sides of the Business Model Canvas. The IRL is intended to quantify risk levels for startups based on evidence gathered through customer development and experimentation.
The document summarizes the journey of four engineers who went through Stanford's Lean LaunchPad class to develop an MVP for a startup idea. Over nine weeks, they tested several hypotheses through customer interviews but were unable to find product-market fit. Their final idea involved personalized recipe recommendations but they determined it was not a viable business due to high customer acquisition costs and an unproven revenue model. They learned important lessons about customer discovery, competition, and the importance of prioritizing revenue.
The document discusses lean innovation and continuous innovation. It argues that continuous disruption requires continuous innovation, and that continuous innovation requires new management tools like lean innovation management. Lean innovation aims to achieve 10x the number of initiatives in 1/5 the amount of time through techniques like the business model canvas, customer development, and agile engineering. It also discusses the need for ambidextrous organizations that can both execute current business models while pursuing breakthrough innovations. Examples are provided of how lean startup techniques have been applied in practice, including a case study of a Stanford student team that applied customer development to validate and pivot their business model based on customer interviews.
The document discusses evidence-based entrepreneurship and investment readiness levels (IRL). It presents the Lean Startup methodology, customer development, business model canvas, agile engineering and hypotheses testing as part of the evidence-based methodology. It discusses how IRL can assess project maturity similar to NASA's technology readiness levels (TRL) by focusing on data from experiments and customer interviews. Several examples are presented of teams applying this methodology in NSF programs to validate hypotheses, the business model and determine IRL.
Over the course of 9 weeks, the team went through multiple pivots to find product-market fit:
1. They started with facial recognition for smart door locks but learned their solution did not fully address parent concerns.
2. Their second pivot was to enterprise access control but customers said tailgating was a bigger problem.
3. Recognizing tailgating risks required surveillance, they pivoted again to surveillance software.
4. After failing to find problem-team fit, they did a complete restart and developed an AI assistant for streamlining similar work tasks. Customer feedback was positive and they identified a potential market of 500k ML professionals.
Becoming an Enterprise SaaS Company | DecisionDesk @ TechPintJohn Knific
DecisionDesk provides SaaS solutions for streamlining digital admissions processes for higher education institutions. After initial success with online portfolios, they pivoted to focus on larger deals, but struggled with a massive implementation that required rewriting their product. They learned that discovery is cheaper than late discovery, experience is better than being scrappy, and to focus on either SMB or enterprise markets, not both. They now have a process of specialized roles to properly execute large deals and target the right decision makers to avoid getting bogged down in price negotiations.
business model, business model canvas, mission model, mission model canvas, customer development, lean launchpad, lean startup, stanford, startup, steve blank, entrepreneurship, I-Corps, Stanford
Class 1 - course overview Berkeley/Columbia Lean Launchpad Xmba 296tStanford University
The document provides an overview of the Lean LaunchPad course, including its objectives, structure, teams, projects, grading, and intellectual property guidelines. The course aims to teach students how to evaluate business opportunities, develop business models, conduct customer discovery and validation, and operate with insufficient data. It focuses on startups with scalable business models and opportunities over $500 million in size.
The document discusses EdgeAI, a startup developing an AI chip with a custom machine learning accelerator and new embedded memory technologies targeting low-power, high-performance edge applications. In early stages, EdgeAI aimed to enable AI vision on battery-powered cameras but faced challenges competing with GPUs. It later found product-market fit enabling solar-powered security cameras by developing a chip that performs inference with no idle power consumption. EdgeAI will validate this approach with pilots and plans to fabricate a second silicon chip and raise seed funding to develop end-to-end prototypes.
business model, business model canvas, mission model, mission model canvas, customer development, hacking for defense, H4D, lean launchpad, lean startup, stanford, startup, steve blank, pete newell, bmnt, entrepreneurship, I-Corps, Security, NSIN, wearable sensors, DOD
This document provides information for mentors of the ENGR 245 course at Stanford University. It outlines the course goals of teaching students how to build venture-scale businesses through customer development and testing business model hypotheses. It describes the student teams, 10-week schedule, and expectations for mentors to meet with their assigned student team every two weeks to provide guidance. Mentors are asked to help students select viable business opportunities and get experience validating their ideas with customers.
This document outlines Steve Blank's development of the Lean LaunchPad methodology for startups. Some key points:
- Blank observed that startups are not smaller versions of large companies, but rather temporary organizations that search for a repeatable and scalable business model.
- He developed the Customer Development process to systematically test business model hypotheses outside the building through customer interviews.
- Eric Ries extended this with Agile Development principles to create the Lean Startup methodology.
- The Lean LaunchPad applies this evidence-based, experiential approach through a 10-week training program to help life science startups validate commercialization opportunities for new technologies.
E-Team Grant Program Webinar PresentationVentureWell
VentureWell is a nonprofit that supports early-stage science and technology innovators through programs, funding, and networking opportunities. The E-Team program provides grants up to $25,000 to multidisciplinary student teams working to commercialize STEM-based inventions with social or environmental impacts. To apply, teams must submit a proposal outlining their technology, business model, team, and work plan. Successful proposals demonstrate technical and market feasibility, commercial potential, team expertise, and measurable social impacts. VentureWell then provides intensive workshops and coaching to help teams validate their ideas and advance their ventures.
The document provides an overview of the I-Corps E245 Syllabus Revision 17 course. The course aims to help teams determine the commercial readiness of their technology through experiential learning and customer discovery. It is taught over several in-person sessions and online lectures, and requires teams to spend significant time outside of class talking to customers. The goal is for teams to develop a go/no go decision about commercial viability and a transition plan if moving forward. Coursework focuses on testing business model hypotheses through customer interactions rather than academic papers or presentations.
This document discusses personal libraries and demand creation for week 5. It provides survey results from users on how they currently organize papers and citations. It also shows the most important factors for users in choosing a paper management system. The document discusses testing Google and Facebook advertising campaigns. It notes some virality from referrals but that collaboration features are not highly engaging yet. It proposes expanding the product from a reference manager to supporting ebooks and other digital content.
The document provides tips for presenting at a hackathon. It recommends identifying customers and problems, forming a team with clear roles, setting expectations, creating milestones and timelines, focusing on delivery speed, validating assumptions, choosing what to prioritize, asking for help when needed, focusing on people's needs, and enjoying the process. It also offers tips for the presentation, including choosing a presenter, practicing, managing time well, and being prepared to answer questions about the problem, solution, uniqueness, traction, business model, investments, risks, timeline, and team. The overall message is to thoroughly prepare your presentation by focusing on the problem and solution, validating your assumptions, and demonstrating what makes your idea unique and how it will
Create Success With Analytics: Living With Technical Debt - Balancing Quality...Aggregage
As a Product Manager, you probably have to deal with technical debt. Regularly. Whether you like it or not - because it can’t be avoided. Unexpected details pop up, as small as UX that needs clean-up, and as big as a previously unforeseen flaw in the infrastructure of a project. We have to accept that nobody gets away without some technical debt. And of course, the longer you take to deal with your technical debt, the more difficult it becomes to address fully.
Feeling frustrated? Fortunately, we can take a step back, gain clarity, and see how the decisions we make impact our technical debt. Then, we can make decisions about how we want to balance technical debt with other priorities. Are we willing to live with some level of technical debt in order to ship product and meet deadlines? Can we mitigate technical debt to get to an MVP faster?
Create Success With Analytics: Living With Technical Debt - Balancing Quality...Hannah Flynn
Here are the questions from the chat:
Q: How do you prioritize technical debt pay down vs new features?
A: There's no single right answer, but some things to consider:
- Understand impact of TD on future development
- Estimate effort for TD vs features
- Involve engineers in prioritization
- Set minimum TD paydown each cycle
- Consider TD that enables new features
- Balance long term health with short term wins
Q: How do you estimate technical debt?
A: A few common ways to estimate technical debt:
- Subjective rating (high, medium, low) of code quality issues
- Time estimates to refactor or fix specific code smells
EcoMachines Incubator - Investment Pitch Day - Cambridge - 17 Oct 13ILIAN ILIEV
EcoMachines Incubator is using Lean Startup principles to transform the early-stage funding model for hardware and engineering companies in the energy and cleantech industries.
EcoMachines Incubator holds Investment Pitch events throughout the year, both in the UK and internationally. These are key to EcoMachines' investment selection process
Attached are the slides from our 1st Investment Demo day in Cambridge, UK in mid-October 2013
Dabur is India's oldest and largest Ayurvedic company managing one of the oldest supply chains in India for over 125 years. It procures raw materials worth $500 million annually from a wide base of vendors and has an integrated distribution network reaching over 2100 stockists and thousands of retail outlets across India. Dabur implemented a direct shipment strategy to bypass warehouses and distribute products directly to retailers, reducing costs and lead times. This helped minimize inventory and transportation costs while improving supply chain efficiency. Dabur's strong distribution network and efficient tactics have helped it succeed and establish barriers against organized competition in India's FMCG industry.
business model, business model canvas, mission model, mission model canvas, customer development, lean launchpad, lean startup, stanford, startup, steve blank, entrepreneurship, I-Corps, Stanford
The document provides an overview of the VentureWell E-Team Grant & Training Program. It begins with introductions to VentureWell and its mission to support student innovators. It then describes the E-Team Program, which provides grants, training and support to multidisciplinary student teams working to commercialize STEM-based inventions. Key details include the application process, eligibility requirements, selection criteria, program benefits and examples of successful companies founded by past E-Teams.
The document outlines an agenda for a two-day workshop on business models and customer development. Day one covers introducing customer development, developing a value proposition and identifying customer segments. Students work on an initial business model canvas and present it. Day two focuses on customer relationships, revenue streams, partners, resources/costs, and concludes with a customer development manifesto. The agenda emphasizes learning customer development strategies through hands-on exercises and student presentations of their business model canvas and customer discovery plans.
Analysis With an Agile Mindset WorkshopKent McDonald
Analysis is often portrayed as eliciting and documenting requirements, frequently in terms that sound a lot like asking people what they want and writing it down. Analysis is about understanding your stakeholders and their needs, identifying the best solution for satisfying those needs in your particular context, and then building a shared understanding of that solution. Requirements play a part in that work, especially around describing the need, but they are certainly not the end product.
In this session, Kent McDonald will guide you through an approach to analysis in an agile manner. You’ll see examples of techniques that will help you understand stakeholders, context, and needs and then determine and describe possible solutions. You’ll then get an opportunity to try those techniques out on a case study. Along the way you’ll find out how to use analysis to determine if you are doing the right thing and how to determine how much analysis is just enough.
Key takeaways:
- Identify and understand potential users with user modeling.
- Determine the appropriate design approach for your project using the Purpose Based Alignment Model.
- Use decision filters to clearly state the desired outcome of your project and provide team with information for decision making.
- Identify and describe backlog items in more detail using collaborative modeling.
Rapid prototyping allows companies to tweak IoT solutions before fully developing products. It enables getting customer feedback to refine solutions and identify requirements. Rapid prototyping is low risk and high reward as it does not require expensive hardware or extensive commitments, but can lead to successful deployments through thorough planning.
Class 1 - course overview Berkeley/Columbia Lean Launchpad Xmba 296tStanford University
The document provides an overview of the Lean LaunchPad course, including its objectives, structure, teams, projects, grading, and intellectual property guidelines. The course aims to teach students how to evaluate business opportunities, develop business models, conduct customer discovery and validation, and operate with insufficient data. It focuses on startups with scalable business models and opportunities over $500 million in size.
The document discusses EdgeAI, a startup developing an AI chip with a custom machine learning accelerator and new embedded memory technologies targeting low-power, high-performance edge applications. In early stages, EdgeAI aimed to enable AI vision on battery-powered cameras but faced challenges competing with GPUs. It later found product-market fit enabling solar-powered security cameras by developing a chip that performs inference with no idle power consumption. EdgeAI will validate this approach with pilots and plans to fabricate a second silicon chip and raise seed funding to develop end-to-end prototypes.
business model, business model canvas, mission model, mission model canvas, customer development, hacking for defense, H4D, lean launchpad, lean startup, stanford, startup, steve blank, pete newell, bmnt, entrepreneurship, I-Corps, Security, NSIN, wearable sensors, DOD
This document provides information for mentors of the ENGR 245 course at Stanford University. It outlines the course goals of teaching students how to build venture-scale businesses through customer development and testing business model hypotheses. It describes the student teams, 10-week schedule, and expectations for mentors to meet with their assigned student team every two weeks to provide guidance. Mentors are asked to help students select viable business opportunities and get experience validating their ideas with customers.
This document outlines Steve Blank's development of the Lean LaunchPad methodology for startups. Some key points:
- Blank observed that startups are not smaller versions of large companies, but rather temporary organizations that search for a repeatable and scalable business model.
- He developed the Customer Development process to systematically test business model hypotheses outside the building through customer interviews.
- Eric Ries extended this with Agile Development principles to create the Lean Startup methodology.
- The Lean LaunchPad applies this evidence-based, experiential approach through a 10-week training program to help life science startups validate commercialization opportunities for new technologies.
E-Team Grant Program Webinar PresentationVentureWell
VentureWell is a nonprofit that supports early-stage science and technology innovators through programs, funding, and networking opportunities. The E-Team program provides grants up to $25,000 to multidisciplinary student teams working to commercialize STEM-based inventions with social or environmental impacts. To apply, teams must submit a proposal outlining their technology, business model, team, and work plan. Successful proposals demonstrate technical and market feasibility, commercial potential, team expertise, and measurable social impacts. VentureWell then provides intensive workshops and coaching to help teams validate their ideas and advance their ventures.
The document provides an overview of the I-Corps E245 Syllabus Revision 17 course. The course aims to help teams determine the commercial readiness of their technology through experiential learning and customer discovery. It is taught over several in-person sessions and online lectures, and requires teams to spend significant time outside of class talking to customers. The goal is for teams to develop a go/no go decision about commercial viability and a transition plan if moving forward. Coursework focuses on testing business model hypotheses through customer interactions rather than academic papers or presentations.
This document discusses personal libraries and demand creation for week 5. It provides survey results from users on how they currently organize papers and citations. It also shows the most important factors for users in choosing a paper management system. The document discusses testing Google and Facebook advertising campaigns. It notes some virality from referrals but that collaboration features are not highly engaging yet. It proposes expanding the product from a reference manager to supporting ebooks and other digital content.
The document provides tips for presenting at a hackathon. It recommends identifying customers and problems, forming a team with clear roles, setting expectations, creating milestones and timelines, focusing on delivery speed, validating assumptions, choosing what to prioritize, asking for help when needed, focusing on people's needs, and enjoying the process. It also offers tips for the presentation, including choosing a presenter, practicing, managing time well, and being prepared to answer questions about the problem, solution, uniqueness, traction, business model, investments, risks, timeline, and team. The overall message is to thoroughly prepare your presentation by focusing on the problem and solution, validating your assumptions, and demonstrating what makes your idea unique and how it will
Create Success With Analytics: Living With Technical Debt - Balancing Quality...Aggregage
As a Product Manager, you probably have to deal with technical debt. Regularly. Whether you like it or not - because it can’t be avoided. Unexpected details pop up, as small as UX that needs clean-up, and as big as a previously unforeseen flaw in the infrastructure of a project. We have to accept that nobody gets away without some technical debt. And of course, the longer you take to deal with your technical debt, the more difficult it becomes to address fully.
Feeling frustrated? Fortunately, we can take a step back, gain clarity, and see how the decisions we make impact our technical debt. Then, we can make decisions about how we want to balance technical debt with other priorities. Are we willing to live with some level of technical debt in order to ship product and meet deadlines? Can we mitigate technical debt to get to an MVP faster?
Create Success With Analytics: Living With Technical Debt - Balancing Quality...Hannah Flynn
Here are the questions from the chat:
Q: How do you prioritize technical debt pay down vs new features?
A: There's no single right answer, but some things to consider:
- Understand impact of TD on future development
- Estimate effort for TD vs features
- Involve engineers in prioritization
- Set minimum TD paydown each cycle
- Consider TD that enables new features
- Balance long term health with short term wins
Q: How do you estimate technical debt?
A: A few common ways to estimate technical debt:
- Subjective rating (high, medium, low) of code quality issues
- Time estimates to refactor or fix specific code smells
EcoMachines Incubator - Investment Pitch Day - Cambridge - 17 Oct 13ILIAN ILIEV
EcoMachines Incubator is using Lean Startup principles to transform the early-stage funding model for hardware and engineering companies in the energy and cleantech industries.
EcoMachines Incubator holds Investment Pitch events throughout the year, both in the UK and internationally. These are key to EcoMachines' investment selection process
Attached are the slides from our 1st Investment Demo day in Cambridge, UK in mid-October 2013
Dabur is India's oldest and largest Ayurvedic company managing one of the oldest supply chains in India for over 125 years. It procures raw materials worth $500 million annually from a wide base of vendors and has an integrated distribution network reaching over 2100 stockists and thousands of retail outlets across India. Dabur implemented a direct shipment strategy to bypass warehouses and distribute products directly to retailers, reducing costs and lead times. This helped minimize inventory and transportation costs while improving supply chain efficiency. Dabur's strong distribution network and efficient tactics have helped it succeed and establish barriers against organized competition in India's FMCG industry.
business model, business model canvas, mission model, mission model canvas, customer development, lean launchpad, lean startup, stanford, startup, steve blank, entrepreneurship, I-Corps, Stanford
The document provides an overview of the VentureWell E-Team Grant & Training Program. It begins with introductions to VentureWell and its mission to support student innovators. It then describes the E-Team Program, which provides grants, training and support to multidisciplinary student teams working to commercialize STEM-based inventions. Key details include the application process, eligibility requirements, selection criteria, program benefits and examples of successful companies founded by past E-Teams.
The document outlines an agenda for a two-day workshop on business models and customer development. Day one covers introducing customer development, developing a value proposition and identifying customer segments. Students work on an initial business model canvas and present it. Day two focuses on customer relationships, revenue streams, partners, resources/costs, and concludes with a customer development manifesto. The agenda emphasizes learning customer development strategies through hands-on exercises and student presentations of their business model canvas and customer discovery plans.
Analysis With an Agile Mindset WorkshopKent McDonald
Analysis is often portrayed as eliciting and documenting requirements, frequently in terms that sound a lot like asking people what they want and writing it down. Analysis is about understanding your stakeholders and their needs, identifying the best solution for satisfying those needs in your particular context, and then building a shared understanding of that solution. Requirements play a part in that work, especially around describing the need, but they are certainly not the end product.
In this session, Kent McDonald will guide you through an approach to analysis in an agile manner. You’ll see examples of techniques that will help you understand stakeholders, context, and needs and then determine and describe possible solutions. You’ll then get an opportunity to try those techniques out on a case study. Along the way you’ll find out how to use analysis to determine if you are doing the right thing and how to determine how much analysis is just enough.
Key takeaways:
- Identify and understand potential users with user modeling.
- Determine the appropriate design approach for your project using the Purpose Based Alignment Model.
- Use decision filters to clearly state the desired outcome of your project and provide team with information for decision making.
- Identify and describe backlog items in more detail using collaborative modeling.
Rapid prototyping allows companies to tweak IoT solutions before fully developing products. It enables getting customer feedback to refine solutions and identify requirements. Rapid prototyping is low risk and high reward as it does not require expensive hardware or extensive commitments, but can lead to successful deployments through thorough planning.
Maximising likelihood of success: Applying Product Management to AI/ML/DS pr...Kevin Wong
According to stats, 85% of Artificial Intelligence (AI) / Machine Learning (ML) / data science (DS) projects fail, which hinders companies' appetite in investing in AI/ML/DS, and holds back data scientists from getting the recognition they deserve. In this talk dated 15 June 2019, Kevin Wong presented a gentle introduction on how he applied a re-invented Product Management approach to AI projects, in order to maximise their likelihood of success.
Are project tracking tools helping or complicating Continuous Improvement Pro...Kubilay Balci
Are project tracking tools helping or complicating Continuous Improvement Projects? presented by Kubilay Balci at 8. Project Management Symposium in Vienna June 7th, 2017.
click here for narratives:
https://www.linkedin.com/pulse/project-tracking-tools-helping-complicating-continuous-kubilay-balci
Agile Practices for Transitioning to SAP S/4HANA® panayaofficial
Attend this webinar for advice on best practices for transitioning to SAP S/4HANA. Topics include:
Uncovering five tips for organizations that want to implement both SAP S/4HANA and agile practices
Understanding the changes that a move to SAP S/4HANA requires
Selecting the best-fit solution to support a transition to SAP S/4HANA
7 mistakes in IoT sales and how to avoid themSimple Hardware
Qualification criteria, discovery depth, and proper pilots definition in Sigfox use cases.
For whom this webinar series? Sales, technical pre-sales, sales, support SO’s and integrators, IoT platforms.
Technical level: intermediate
Watch the recording here:
https://www.youtube.com/watch?v=KqZ5mOANAlM
Read blog post here: https://simplehw.eu/7-main-pitfalls-of-iot-sales/
This is a presentation which i presented at my college on The 2 month summer internship done by me at Value Edge , Delhi during mid april 2009 to mid june 2009
How to Turn Raw Data into Product Revenue by Retrofit PMProduct School
Most companies have a goldmine of data, yet lack the ability to know what to do with it. In this talk, Monica shared perspective on how to evaluate data, package it, and turn it in to additional revenue streams.
Main takeaways:
- Identify use cases for data.
- Turn those use cases in to product offerings.
- Create a pricing model & collect revenue.
The document provides information on the RoboPorter team working on an automated consolidated reporting solution. It lists the team members and their roles. It then describes the problem of manual consolidated reporting currently used by single and multi-family offices. The proposed solution is to use machine learning and natural language processing to automate reporting and make it more accurate. It provides details on the business model, target customers, competitors, and revenue model which involves subscription fees for the automated reporting software.
Webinar for September 2019 - Organisational Design and StrategyThe Digital Insurer
The document summarizes a panel discussion on organizational design and strategy for digital insurers. The panelists discussed topics like critical success factors for innovation projects, digital hiring trends, ingredients for organizational agility, structuring IT for a digital insurer, and knowledge gaps between business and IT teams. Participants provided feedback through polls on these topics and their interest in future events from The Digital Insurer.
Measuring Performance in a Future Media WorldOrigami Logic
As brands expand their use of digital media and adtech to engage and build relationships with consumers, the ability to translate performance data into meaningful insights about what’s working and what’s not has become an essential part of marketing success. According to a new report published by Brand Innovators and Origami Logic, however, only 3 out of 10 marketers currently excel in their efforts to extract insights from their marketing performance data. We’ll dive into the survey findings and explore why 80% of marketers are putting more focus on measuring performance in 2017. You’ll walk away with practical tips about how your organization can improve its measurement effectiveness.
This document discusses the importance of design and user experience (UX) for startups. It provides examples of how UX design can help startups succeed by addressing common reasons for startup failure such as lack of product-market fit, running out of cash, and poor marketing. The document also provides case studies of startups that Interactivism worked with, including how UX design helped Scoutables validate their product idea and differentiate Cisco Metacloud's offering.
Hiring across Technology Space in Bangalore? This might be the perfect opportunity for you. Grab on to this opportunity and hire the best talent in the country.
Startup Mashup powered by MyRefers is an event where in a single day, we rank profiles and are able to get a large no. of high quality hires (experienced folks from IIT/NIT/NSIT/BITS/DTU etc ).
We have done 6 events till date , all in Delhi and it has proven to be a super successful format. The specs and stats of the previous events can be found in the presentation.
NUS-ISS Learning Day 2018- Productization exploiting it for digital transfo...NUS-ISS
The document discusses productization and digital transformation. It provides 5 keys to successful digital projects: 1) shift to a customer service mindset, 2) add a product mindset, 3) create an inspiring product vision, 4) focus on delivering customer value, and 5) determine the right metrics. The presentation uses examples from companies like Amazon to illustrate how adopting a product mindset focused on customer needs can lead to sustainable differentiation and success with digital projects. It emphasizes experimenting, failing fast, and continually learning to meet evolving customer demands.
1. The document outlines 4 laws of tech product economics: the development team will never be big enough so prioritization is crucial; all profits come from additional users/copies so focus on segmentation; technology alone is not the product and whole solutions must be offered; and strategy and discovery cannot be outsourced and require judgment.
2. The first law emphasizes ruthless prioritization and managing "magical thinking" to focus on finishing critical tasks.
3. The second law notes profits come from additional users/copies, so the focus should be on segments rather than individual deals.
The document introduces the importance of user experience and how companies are increasingly prioritizing it as a strategic advantage. It discusses how the focus on customers has become imperative in today's competitive landscape, with 97% of companies considering customer experience a strategic priority. Companies that excel at user experience see benefits like a 14.4% increase in willingness to purchase from customers. The document also outlines VLG's user experience design process and recommends companies invest 10-20% of project budgets into UX.
The document provides information about an online M.Tech degree program in Artificial Intelligence and Machine Learning offered by Intellipaat in collaboration with IIT Jammu. The 2-year program aims to provide in-depth knowledge of core AI and ML skills like Python, SQL, Apache Spark, neural networks etc. It focuses on building a strong profile for professionals and aspirants in the fast growing domain of AI and ML. The program curriculum includes courses across 4 semesters covering topics like machine learning, deep learning, image processing etc.
This document provides an overview of DevOps and how to adopt a DevOps approach. It discusses that DevOps aims to shorten the systems development life cycle and provide continuous delivery with high software quality. The document outlines that adopting DevOps involves changes to an organization's people, processes and technologies. It provides strategies for building a collaborative culture and implementing shared goals and metrics. It also discusses implementing efficient processes for continuous integration, delivery, testing and monitoring. The document recommends technologies like infrastructure as code, collaboration tools, and release automation to support the DevOps approach.
Team Networks - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, networks
Team LiOn Batteries - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, LiOn Batteries
Team Quantum - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Quantum
Team Disinformation - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Disinformation
Team Wargames - 2022 Technology, Innovation & Great Power CompetitionStanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Wargames
Team Acquistion - 2022 Technology, Innovation & Great Power Competition Stanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, Acquistion
Team Climate Change - 2022 Technology, Innovation & Great Power Competition Stanford University
Technology Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, climate
The document describes a team's efforts to commercialize a new protein quantification technology called PLA-Seq. After initially thinking the technology's value propositions of lower cost, faster throughput, and lower sample volume would appeal to pharmaceutical and personalized health companies, the team conducted customer interviews and learned accuracy was more important than cost to most customers. They also found their target markets should be preclinical biotech and academia rather than personalized health or CROs. The team incorporated their business and pivoted their marketing strategy and funding plans accordingly based on learnings outside of the building.
The document summarizes the development of Invisa Bio over 10 weeks as they pivoted between different medical applications and solutions for their self-assembling medical device technology. They initially focused on manufacturing and delivery but shifted to leveraging drug delivery mechanisms. They considered applications in cardiology, neurology, and orthopedics before focusing on brain aneurysms based on feedback from physicians. The company incorporated, raised funding, and began shadowing doctors to further develop their technology to address unmet needs in difficult to reach areas.
(1) The document describes the journey of a team developing a saffron supplement product to address mental health issues like anxiety and depression.
(2) It started with the goal of targeting adults aged 18-40, but through customer interviews and testing, they learned that teenagers were more interested in an anti-anxiety gummy product.
(3) Key lessons included the challenges of building the right team, navigating advice, knowing when enough customer feedback has been received, and setting individual and project milestones. The team is now continuing work over the summer to further develop the product.
Team Army venture capital - 2021 Technology, Innovation & Great Power Competi...Stanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, Army venture capital
Team Army venture capital - 2021 Technology, Innovation & Great Power Competi...Stanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve Blank, Army Venture capital
Team Catena - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, economic coercion,
Team Apollo - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, space force
Team Drone - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, c3i, command and control
Team Short Circuit - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, semiconductors
Team Aurora - 2021 Technology, Innovation & Great Power CompetitionStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, Army venture capital
Team Conflicted Capital Team - 2021 Technology, Innovation & Great Power Comp...Stanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, venture capital
Lecture 8 - Technology, Innovation and Great Power Competition - CyberStanford University
Technology, Innovation and Great Power Competition,TIGPC, Gordian knot Center, DIME-FIL, department of defense, dod, hacking for defense, intlpol 340, joe felter, ms&e296, raj shah, stanford, Steve blank, AI, ML, AI/ML, china, unmanned, autonomy, Michael Sulmeyer, cybercom,USCYBERCOM
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
This presentation was provided by Rebecca Benner, Ph.D., of the American Society of Anesthesiologists, for the second session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session Two: 'Expanding Pathways to Publishing Careers,' was held June 13, 2024.
1. Cutting edge wireless
sensor chip looking for a
perfect vertical application
in IoT space
Recruiting solution to improve
pre-screening for candidates
without relevant work
experience
From week 1... To week 10...
92 interviews
8 industries
5 iterations +
1 major pivot
500+ hours invested
30+ hypothesis
invalidated
Monolets CareerFIT
2. We started the LLP experience helping a Berkeley PhD commercialize a new IoT
chip
50x cheaper
Help in finding an application to validate market appetite for the technology
20x smaller
20x less power
consumption
3. The team had wide experience in IoT-)
Ilya Bukeev Borja EdoKiran Kondru Eric Manalac
Undergrad:
Physics and Math
Grad:
FTMBA @ Haas
Undergrad:
Electrical engineering
Grad:
EWMBA @ Haas
Undergrad:
Civil engineering
Grad:
FTMBA @ Haas
Undergrad:
Math and CS
Consultant @
McKinsey Moscow
Consultant @
Accenture Madrid
Engineer @
Intel Sacramento
Mobile Games Dev
(Top 3 GMIC)
4. However, our LLP journey was not as easy as we thought it would be
1 2 3 4 5 6 7 8 9 10 11 12
Team’smood
+
-
Week
PIVOT AWAY
FROM MONOLETS
Brainstormed
a long list of
potential
applications
Wine
solution is
shut down
Big Biotech is
interested in
knowing more
Biotech discards
Monolets
Realize we don’t speak the
customers’ language
“What is your network
stack?”
Start exploring first
application: Wine
Temperature
Changing
discovery process
Let us tell you our story
5. First week, first challenge and first
lesson
Getting ready to research and talk to people
Founder doesn’t want to share info
We have to research for similar products in the market.
Shallow knowledge of product, market pains and
competitive advantage
LEARNING 1
Lack of support from
founder makes it really
hard to gain expertise, set
interviews and even talk to
customers
6. - Humidity
and
temperature
sensing
Refineries
Week 0: several parallel business model canvases
to explore
On week 1 team was
excited to explore
multiple industries
For each
application team
designed a
separate BMC
Monolets
- Air quality monitoring
- Preventive maintenance
of equipment
- Disaster prevention
Smart cities
- Air quality
monitoring
- Smart
parking
Supply chain
- Food freshness
monitoring
- Vaccines monitoring
- Industrial assets tracking
Wine and beer
- Wine bottle history
tracking
- Craft beer quality
tracking
Agriculture
- Smart
sneakers
- Smart sport
clothes
Apparel
7. … and spent 4 weeks interviewing players in several industries and constantly
redrawing business canvas
Value proposition for Oil & Gas Value proposition for Pharma
Value proposition for Agricultural IOT
8. Refineries
Week 5 weeks passed: no success….
Based on 50+
interviews team
rejected all available
solutions
Team was
exhausted,
demoralized and
completely stuck
Monolets
Smart cities
Supply chain
Already done or
our tech does
not help
Wine and beer
Agriculture Apparel
?
Strong competition or our
tech does not help
Established
collaboration
with Nike
No burning need
Small market of
upscale wine
Long sale cycle
No advantage over
existing technology
No burning need
Very fragmented
market
9. In week 6, we officially admit defeat on finding the killer app
Failed testing idea after idea
until one showed market interest
How have other
companies with a new
technology found the
killer applications?
Do you think you are
smarter than market?!
Wine Supply
Chain
Oil &
Gas
Vineyards
BioTech Cold
Chain
Manufacturing
Smart Cities
random?
10. We realized that many companies with a technology breakthrough had let their
customers tell them which ones where the killer applications
Build a horizontal platform and let users build
applications on top of it
Market your new breakthrough through press
release and let customers come to you
Press release
1000s of patents on usage
$800m in annual revenues
Press release for exact same
Product (low power IoT chip)
Focus on HW technology: too technical.
The team had neither expertise nor support from
founder to speak the new customers’ language
Works well with big corporations
Technology not there yet
Founder unwilling to disclose any info
New interviews: much more
technical… and painful
Customer: What
is your network
stack??
Best practice 1: Best practice 2:
11. Week 4-6
LEARNING 2
A new technology with many potential
applications has a different discovery process.
Let the customer tell you the killer applications
instead of exploring one by one
LEARNING 3
The team has to have expertise in the product to
be able to pivot and talk to customers with a
minimum of credibility, especially if you’re
selling HW
12. Week 7: We finally Pivot
LEARNING 5
Choose the project
wisely: both in terms of
expertise and passion
LEARNING 4
Sunk costs are sunk.
Don’t get attached to an
idea if it is not working!
Team expertise
Teampassion
Recruiting platform for
candidate skills
assessment
P2P career advising platform
Team picked
this idea for
pivot
Review improvement solution for specialized
products (roller skates, wet suits, etc)
Community based craiglist
13. - Companies with large volumes
of applicants need to reject a lot
of people before interviews
- Hiring managers (or HRs) have
difficult time to differentiate
candidates without prior relevant
experience
Week 7. Based on interviews we decided to focus on the most critical process
part - pre-screening
Standard job application process (from candidate’s perspective)
Optional telephone
interview
- MBA switching jobs apply to
20-88 positions
- Application process takes up to
1 hour for each company
- Switching candidates try to
show relevant skills in cover
letter
- Only about 10% of applications
are translated into interviews (for
MBAs switching to another role)
- There is no feedback after
reject
- Interviews are stressful
- No feedback after
unsuccessful interviews
- Many small companies
struggle to attract large amount
of applicants
Painpointsof
candidate
Painpointsof
hiringmanager
- Interviews are taking a lot of
time
APPLICATION
Preparation of CV
Preparation of cover letter
Application online
PRE-SCREENING
HRs and/or hiring managers
select candidates for
interview
INTERVIEWS
JOB OFFER
We focused on Pre-screening phase
● Based on our personal painful experience
● Based on confirmed pain points
● No company is solving the problem
- Job offer is expiring quickly
- Significant share of offers
declined
We believe that
hiring managers
should be targeted
before candidates
14. Week 8: we narrowed down with candidates
Our first customers
● MBAs
● Applying to PM
● Without PM
experience
● Tech company
Roles
● Product management
● Project management
● Business analyst
● Supply chain manager
● ...
Candidate types
● MBAs switching roles
● Non-MBA professionals switching roles
● Recent college graduates
Industries
● Technology
● Banking
● Consulting
● NGO
● ….
After experience with
Monolets we decided
to narrow down as
soon as possible
Selection was based
on ease of access
and significance of
customer need
15. MVP was critically important for interviews
To 10 pages pdf report with real candidate assessment on week 7...
From abstract wireframe
on week 6….
● Was too abstract
● Did not help to test
hypotheses
● Focused on critical product aspect (assessment + summary)
● Hiring managers provided specific feedback
16. Main interview learnings
careerFITExpectations Interview discoveries
MBAs switching to new roles would like to
reduce time spent on applications
Main concern is not time spent but
conversion rate: application -> interview
PMs skills are universal so we can use
similar assessments for different
companies
Startups often don’t look for PMs with
experience on large established products.
They need different set of skills
PM hiring managers would like to have
assessment additional to CV and Cover
Letter.
Report should include summary scores +
raw data for potential cross check
Confirmed.
Hiring managers are willing to have
additional assessment but would like
reliable summary scores to safe effort
Rejection
Confirmation
17. Next steps
Where we are right now and next steps
Team members are planning to pursue career options other than CareerFIT
Part of the team is considering to continue with CareerFIT
Current status
Team partially finished with right side of BMC
Gained good insights on the pains experienced by HR/Hiring managers and switching
MBAs -> found initial validation for our MVP
Team has 3rd iteration of MVP based on customer interviews and feedback
We don't have the data today to ascertain the product market fit for our product but
we believe that there is one (at least for large and mid size tech companies)